INTERBANK RATE AND THE LIQUIDITY OF THE MARKET

Document Sample
INTERBANK RATE AND THE LIQUIDITY OF THE MARKET Powered By Docstoc
					                              Banco Central de Chile
                              Documentos de Trabajo

                                Central Bank of Chile
                                  Working Papers

                                               N° 516

                                            Abril 2009




                    INTERBANK RATE AND THE
                    LIQUIDITY OF THE MARKET
 Luis A. Ahumada              Álvaro García               Luis Opazo               Jorge Selaive




La serie de Documentos de Trabajo en versión PDF puede obtenerse gratis en la dirección electrónica:
http://www.bcentral.cl/esp/estpub/estudios/dtbc. Existe la posibilidad de solicitar una copia
impresa con un costo de $500 si es dentro de Chile y US$12 si es para fuera de Chile. Las solicitudes se
pueden hacer por fax: (56-2) 6702231 o a través de correo electrónico: bcch@bcentral.cl.

Working Papers in PDF format can be downloaded free of charge from:
http://www.bcentral.cl/eng/stdpub/studies/workingpaper. Printed versions can be ordered
individually for US$12 per copy (for orders inside Chile the charge is Ch$500.) Orders can be placed by
fax: (56-2) 6702231 or e-mail: bcch@bcentral.cl.
                        BANCO CENTRAL DE CHILE

                         CENTRAL BANK OF CHILE


La serie Documentos de Trabajo es una publicación del Banco Central de Chile que
divulga los trabajos de investigación económica realizados por profesionales de esta
institución o encargados por ella a terceros. El objetivo de la serie es aportar al debate
temas relevantes y presentar nuevos enfoques en el análisis de los mismos. La difusión
de los Documentos de Trabajo sólo intenta facilitar el intercambio de ideas y dar a
conocer investigaciones, con carácter preliminar, para su discusión y comentarios.

La publicación de los Documentos de Trabajo no está sujeta a la aprobación previa de
los miembros del Consejo del Banco Central de Chile. Tanto el contenido de los
Documentos de Trabajo como también los análisis y conclusiones que de ellos se
deriven, son de exclusiva responsabilidad de su o sus autores y no reflejan
necesariamente la opinión del Banco Central de Chile o de sus Consejeros.



The Working Papers series of the Central Bank of Chile disseminates economic
research conducted by Central Bank staff or third parties under the sponsorship of the
Bank. The purpose of the series is to contribute to the discussion of relevant issues and
develop new analytical or empirical approaches in their analyses. The only aim of the
Working Papers is to disseminate preliminary research for its discussion and comments.

Publication of Working Papers is not subject to previous approval by the members of
the Board of the Central Bank. The views and conclusions presented in the papers are
exclusively those of the author(s) and do not necessarily reflect the position of the
Central Bank of Chile or of the Board members.




                  Documentos de Trabajo del Banco Central de Chile
                    Working Papers of the Central Bank of Chile
                                  Agustinas 1180
                   Teléfono: (56-2) 6702475; Fax: (56-2) 6702231
          Documento de Trabajo                                                 Working Paper
                N° 516                                                            N° 516

                            INTERBANK RATE AND THE
                            LIQUIDITY OF THE MARKET

  Luis A. Ahumada                 Álvaro García                  Luis Opazo                   Jorge Selaive
   Banco Central de Chile        Banco Central de Chile        Banco Central de Chile    Banco de Crédito e Inversiones




Resumen

En este trabajo estudiamos la dinámica diaria de la tasa interbancaria en Chile, con especial
atención al rol de la liquidez provista a través de depósitos bancarios y operaciones de mercado
abierto realizadas por el Banco Central. El principal objetivo de este trabajo es evaluar la
información contenida en datos desagregados y de alta frecuencia de esas variables. Los
principales resultados se encuentran relacionados a la significancia económica de la velocidad
de convergencia, los efectos calendario y de las operaciones con pacto de retroventa (repo). El
Banco Central juega un rol más importante drenando que inyectando liquidez por medio de
operaciones monetarias discrecionales. Sin embargo, no hay asimetrías en términos de la
efectividad de las inyecciones y drenajes discrecionales dependiendo de la liquidez del
mercado. Adicionalmente, los bancos de mayor tamaño son menos receptivos a las operaciones
monetarias, mientras que los bancos pequeños son los más sensibles a dichas operaciones, lo
cual es consistente con el tradicional rol de estas categorías de bancos en la provisión de
liquidez en el mercado interbancario. Finalmente, los depositantes privados no juegan un rol
importante en la dinámica de la tasa interbancaria durante el período muestral.




Abstract

In this paper we study the dynamics of the interbank rate in Chile, with special attention to the
role of liquidity provided by private depositors and by the central bank’s open market
operations on a daily basis. The main aim of this paper is the use of disaggregated and high
frequency data on such variables. The most relevant findings are related to the statistical and
economic significance of speed of convergence, calendar effects and repos operations. The
Central Bank plays a more important role injecting than draining liquidity through discretionary
operations. However, there are not asymmetries in terms of the effectiveness of the
discretionary injections and drainages operations depending on the liquidity market status. In
terms of effect by class of bank, large- and medium-size banks are less receptive to monetary
operations; by contrast small-size banks are the most responsive, which is consistent with its
traditional position as a liquidity demander. Finally, private deposits do not play an important
role on the dynamics of the interbank rate during the sample period.



_______________

  We thank Felipe Alarcón, Matías Bernier and Jorge Pérez for helpful suggestions, participants at internal seminars
in Central Bank, and Carmen G. Silva who collaborated in a preliminary version of this work. We are also grateful to
the Department of Open Market Operations for sharing with us the data used in this work. All errors are ours. E-mail:
lahumada@bcentral.cl; agarcia@bcentral.cl; lopazo@bcentral.cl; jselaiv@bci.cl.
1. Introduction
       The interbank money market rate (ir) stands at the shortest end of the yield
curve, and is the operational target for the monetary policy rate (mpr).
Therefore, understanding the factors behind the dynamics of the ir is relevant
not only for participants in the interbank market, but also for private investors
and monetary authorities. Indeed, the ir is a key benchmark for interest rates in
the short-term money market and its movements may have effects on the whole
term structure (Taylor and Williams, 2008 among others). Moreover, the
interbank market represents the first stage of the monetary transmission
channel, where monetary policy actions first come into contact with the rest of
the financial system. An effective monetary policy requires that the overnight
interest rate remains “at an average of around” the mpr. 1
       In this paper we study the dynamics of the ir in Chile, giving special
attention to the role of the liquidity provided by private depositors and by the
Central Bank’s open market operations. Our paper extends the previous
literature mainly in three aspects. Firstly, we study the effect of liquidity
provision by both the central bank and private depositors on the dynamics of
the ir. To the best of our knowledge, this paper is the first attempt in the
literature to broadly incorporate this dimension into the analysis of the ir.
Secondly, we provide novel evidence on the behavior of the ir in an emerging
economy, which is useful to fill the gap created by preceding literature mainly
focusing on industrial countries.2 Finally, we take a systematic approach that
involves both the time series and panel data dimensions, allowing us to have a
broader picture of the factors behind the high frequency dynamics of the ir.
       The liquidity of the market affects directly the amount of resources that
commercial banks have at their disposal and which they will consequently be
willing to lend in the interbank market. However, with the exceptions of Wurtz
(2004) and Hamilton (1996),3 previous empirical studies have not considered the
effect of daily liquidity conditions on the analysis of the ir. In fact, the literature

1
    The functioning of the Chilean interbank market is similar in structure to US and Euro area cases. Appendix 1
describes in depth technical details related to the functioning of the interbank market in Chile.
2
    Evidence for the European overnight interbank rate (EONIA) and for the federal funds rate can be found in Spindt
and Homeister (1988), Hamilton (1996), Balduzzi et al. (1997, 1998), Gaspar (2004), Nautz and Offermanns (2006),
Prati et al. (2003) and Cocco et al. (2009), among others.
3
    These authors consider the daily reserve surplus, i.e. current account holdings minus reserve requirements, as an
indicator of the liquidity conditon.



                                                                                                                   1
generally analyzes the functioning of the interbank market using a general
framework in which banks’ reserve positions are affected by random shocks and
where the interbank market allows banks to fulfill their monthly reserve
requirement (e.g., Ho and Saunders, 1985; Freixas et al, 2000; Allen and Gale,
2000). Within this scheme, an important number of empirical papers have
studied the effect of periodic events affecting banks’ reserve positions. Indeed, a
bulk of empirical evidence points out that variables like the last day of the
reserve maintenance period, the last day of the month, the prior day to a Holy
day or the day of the monetary policy meeting are relevant for explaining the
daily dynamics of the ir (Hamilton, 1996; Sarno and Thornton, 2001; Prati et
al., 2003; Moschitz, 2004; Nautz and Offermans, 2006; Benito et al., 2007).
       As mentioned above, we make use of a unique database containing detailed
information about the different types of open market operations as well as
deposits by depositors at the bank level. This dataset allows us to test the role
of money market operations through permanent credit lines and repos. Liquidity
provision by the central bank usually involves drainage and injection of funds
through repo operations at mpr (discretionary operations hereafter), combined
with permanent draining and injection of funds at mpr – 25 bps and mpr + 25
bps, the “floor” and “ceiling” of market rates around the target, respectively.
The use of discretionary operations, instead of credit facilities, could be
interpreted as a high degree of commitment of the central bank to take the ir
close to the mpr, which could lead to the gap between these rates being closed
faster. In this line of research, Nautz and Offermanns (2006) explore the role of
the repo auction format in the Euro zone, and Prati et al. (2003) study central
banks’ operating procedures and intervention styles for the Euro zone and G-7
countries.
       The modeling strategy for the time series follows Sarno and Thornton
(2001), and Nautz and Offermanns (2006), who employ an error correction
model to characterize the dynamics of the ir allowing for non-linearities.4 Given
that we have high frequency data of the monetary policy operations and
deposits at banks, we complement the strategies of these studies by evaluating
the economic impact of different types of interventions on the short run
dynamics. We also evaluate whether deposits from pension funds (PF hereafter)

4
    Benito et al. (2007) follow a more statistical approach to model the EONIA. They employ several models containing
jump components – for instance ARCH-Poisson-Gaussian process.



                                                                                                                   2
have a different impact on the ir from that of the others depositors. We
supplement time series estimations with panel data analysis that exploits the
variation of the ir across banks. The estimation strategy is a standard fixed
effect panel using instrumental variables to control for potential endogeneity of
some regressors.
   Our results indicate that the ir and the mpr move together very closely and,
when these variables deviate from each other, the speed of convergence is
around 30% per day. In term of the explanatory variables, the calendar effects
and open market operations –especially the discretionary operations- are the
most relevant in explaining the dynamics of the ir. With respect to the calendar
effects, they play an important role on the dynamics of the ir –which is
consistent with previous findings in this area- a situation that poses questions
on which frictions drive this finding. Regarding the relevance of market liquidity
provided by the central bank, we find that the central bank played an
important role during the sample period, while private depositors do not help to
significantly improve the explanation of the dynamics of the ir. For example, if
we consider the average daily monetary operation and long-run PF’s deposits,
the effect of discretionary injections, drainages and long-run PF’s deposits on
the ir is 1.7, 3.4, and 0.05 bps, respectively. The permanent credit lines are not
statistically significant; this situation could be due to the fact that this
instrument is available on a daily frequency and, therefore, the market has
internalized its operation in the valuation of the ir. The results also show a
more active role of central bank injecting than draining liquidity. The effect of
draining and injection operations on the ir are quite similar, but the magnitude
of drainages are close to two time the injections. At the bank level, the most
relevant asymmetry is due to the distinction of banks according to their size.
Concretely, the large banks are less sensitive to monetary operations –which
could be associated to their condition of liquidity providers- meanwhile small-
size banks are the most responsive to central bank’s instruments.
   The rest of this paper is structured as follows. Section 2 presents the data.
Section 3 performs time and panel data estimations. Section 4 concludes.




                                                                                3
2.          Data
2.1.         Description
       In this paper we use three main data sets. The first consists of detailed
information for each loan granted in the Chilean interbank market on a daily
basis for the period of June 2006 to August 2008 (532 trading days). The data is
from the Central Bank of Chile5 and include 29 banks that are active traders in
the money market. It also identifies lenders and borrowers, as well as the
interest rate and volume involved in each operation.
       With the previous information, we compute the daily ir at which banks
borrow from each other as the weighted average of its operations for each day.
Similarly, we construct the aggregated ir as the weighted average of the
individual ir, where the weights are computed as the ratio of the volume
involved in each operation to the aggregated traded volume.
       The other two datasets contain information with proxies of the liquidity
conditions at the banking system. The first dataset comprises daily information
of the operations carried out by each bank with the Central Bank of Chile (i.e.,
repos, auctions of promissory notes, etc.). The second dataset contains
information on deposits in commercial banks grouped by PF and other
investors. This last dataset was built with information provided by the
Superintendencia de Bancos e Instituciones Financieras (SBIF) and the
Superintendencia de Pensiones (SP).
       We consider several other sources of information for external and domestic
variables that we include in the analysis as factors that could potentially affect
the aggregated liquidity conditions. On the external side, we use the Libor-OIS
spread and the VIX. On the domestic side, we consider a measure for shocks on
the expected mpr, corresponding to the difference between the expected mpr
derived from forward contracts and the current mpr.


2.2.         The Interbank Rate and the Overnight Money Market
       Within the sample period, the ir has followed the policy rate closely,
generally being only 1.8 bps above the mpr (see Figure 1a). In this dimension,
the Central Bank has been successful in steering the short-term interest rates

5
    The functioning of the Chilean interbank market is similar in structure to U.S. and European area cases. Appendix 1
describes in depth the technical details related to the functioning of the interbank market in Chile.



                                                                                                                     4
towards the mpr, in spite of the large variations of the mpr during the sample
period—from 5.00 to 8.25 percent and the financial turbulences derived from the
sub-prime crisis. Indeed, there are only a few episodes where the ir decouples
significantly from the mpr and these episodes have been highly transitory: for
instance, mid-2007 (see Figure 1b). Nonetheless, there is considerable
heterogeneity of these variables across time. In fact, the average deviation
during 2007 was close to 5 bps which contrasts with the 0.5 bps observed during
years 2006 and 2008 (Table 1). And, in terms of volume in the interbank
market, its peak in the sample occurred in 2007 (30% and 15% higher with
respect to 2006 and 2008, respectively), which suggests a high appetite for
liquidity coming from commercial banks at the beginning of the financial
turbulences derived from the sub-prime crisis.


                                                                                                                                                                                              Figure 1
                                                                    Chilean Monetary Policy Rate and Interbank Rate
                                                                      Panel (a)                                                                                                                                                                       Panel (b)
                                                    2006.06-2008.08                                                                                                                                                                         2007.07-2007.09
 8,50                                                                                                                                                                                                  5,95

 8,00
                                                                                                                                                                                                       5,75

 7,50
                                                                                                                                                                                                       5,55
 7,00
                                                                                                                                                                                                       5,35
 6,50

 6,00                                                                                                                                                                                                  5,15

 5,50                                                                                                                                                                                                  4,95

 5,00
                                                                                                                                                                                                       4,75
 4,50
                                                                                                                                                                                                              03-07-2007


                                                                                                                                                                                                                           13-07-2007


                                                                                                                                                                                                                                        23-07-2007


                                                                                                                                                                                                                                                     02-08-2007


                                                                                                                                                                                                                                                                  12-08-2007


                                                                                                                                                                                                                                                                               22-08-2007


                                                                                                                                                                                                                                                                                                  01-09-2007


                                                                                                                                                                                                                                                                                                               11-09-2007


                                                                                                                                                                                                                                                                                                                            21-09-2007
        2006,06
                  2006,07
                            2006,08
                                      2006,10
                                                2006,11
                                                          2007,01
                                                                    2007,02
                                                                              2007,04
                                                                                        2007,05
                                                                                                   2007,07
                                                                                                             2007,08
                                                                                                                       2007,10
                                                                                                                                 2007,11
                                                                                                                                           2008,01
                                                                                                                                                     2008,02
                                                                                                                                                               2008,03
                                                                                                                                                                         2008,05
                                                                                                                                                                                   2008,06
                                                                                                                                                                                             2008,08




                                                                                                  ir                    mpr                                                                                                                                             ir                  mpr


 Source: Authors’ calculations based on information provided by the Central Bank of Chile.




                                                                                                                                                                                                                                                                                                                                         5
                                                          Table 1
                      Interbank Market’s Descriptive Statistics (2006-2008)
                                                 2005          2006            2007         2008        2005-2008

           ir (%)                                 3.91          5.02           5.35         6.72            5.61

           ir - mpr (bps)                         0.8           0.5             4.8         -0.5            1.8
           Average Volume                        262.8         256.7           333.5       290.9           294.8
        Note: Interbank rate is expressed in percent points, the difference between the interbank and the target
        rate in basis points. Average interbank volume is in billions pesos.

       Source: Authors’ calculations based on information provided by the Central Bank of Chile.



       In the previously mentioned decoupling of mid-2007 (see Panel (b), Figure
1), for almost an entire month the ir was systematically above the mpr, with a
spread that reached a peak of 21 bps at the beginning of September 2007. This
decoupling could be related to different drivers happening simultaneously,
making the identification of the incidence of these factors an extremely difficult
task. First, the Chilean and international financial markets were severely hit by
turbulences derived from the sub-prime crisis.6 Second, on August 9th the
maximum regulatory limit on foreign assets held by PF was increased from 30
to 35 percent of the total portfolio.7 Finally, there were high expectations of an
increase of the mpr on the monetary policy meeting of September 13th of that
year and commercial banks seemed to anticipate a 25 bps increase in that
meeting.
       On the quantity side, Table 2 presents some descriptive statistics of the open
market operations during the sample period. A few points deserve to be
mentioned. First, the average interbank operations are of similar magnitude to
most of the monetary operations managed by the Central Bank.8 Second, the
sample period considers the significant activity of both liquidity and draining
discretionary operations, which will allow us to identify if the market responds
differently to these operations. Third, if we compare the frequency of liquidity
and drainages with the ir-mpr spread, it is not evident that discretionary or


6
    Indeed, during August 2007 the Chilean stock market experienced a phase of unusual high volatility, falling almost
10% between the 9th and the 13th of August and fully recovering these losses in the following four trading days.
7
    It was common in this period to observe Chilean money managers declaring in the current press, the possibility that
pension funds could be affecting market liquidity. PF accounts on average around 20% of total deposits held by
commercial banks.
8
    The average of each type of operation is calculated using only the days that register each type of operation.



                                                                                                                     6
permanent operations work in a counter-cyclical fashion with respect to degree
of decoupling of the ir –i.e., injections (drainages) relatively more important
when the ir is above (below) the mpr. In this sense, the frequency of injections
or drainages of liquidity does not seem to depend only upon the ir running
above or below the mpr. This could suggest that market liquidity condition is
not only measured by the ir – mpr spread. We take this situation into account
in our econometric estimations by using several controls. However, and just for
expositional purposes, we define a liquid market the cases when the ir<mpr and
vice versa.
                                                     Table 2
              Descriptive Statistics of the Interbank Market (2006-2008)
  Average Operation Volume (in billions pesos)

  Variable                                            Mean                  Median                Maximum
    Interbank Operations                                    288.6                  286.2                  658.6
    Discretional Injections                                 297.0                  242.9                1,202.5
    Discretional Draining                                   600.5                  545.6                1,397.2
    Permanent Liquidity Facilities                           47.5                    21.9                 513.7
    Permament Deposits Facilities                           266.7                  195.7                1,253.1

                                                                       Illiquid Market         Liquid Market
                                                                          Conditions             Conditions
  Share of the Time with Positive Op                 Overall            ( ir > mpr )           ( ir < mpr )

    Interbank Operations                                    100%                   100%                   100%
    Injections                                               22%                    25%                    15%
    Draining                                                   6%                     7%                     5%
    Permanent Liquidity Facilities                           88%                    89%                    91%
    Permament Deposits Facilities                           100%                   100%                   100%

  Note: Discretional Operations excludes swap operations. The average only consider days with positive operations

 Source: Authors’ calculations based on information provided by the Central Bank of Chile.




2.3.      Bank-Level information
   The aggregate information allows us to understand global and domestic
factors behind the dynamics of the average ir, but it hides the heterogeneity of
the liquidity needs of each commercial bank. For this reason, we also explore
the cross-section dimension of the data to determine whether the adjustment of
the ir depends on specific characteristics of each bank.


                                                                                                                    7
        To illustrate the degree of heterogeneity of the ir at the bank level, Figure 2
contains the aggregate ir – mpr spread (left panel) and the spread for each bank
(right panel) from June 2006 to October 2008. It is interesting to notice that the
ir exhibits significant variation across banks, covering practically all the range
of +/-25 bps, with a few exceptions where the spread exceeds the ceiling of +25
bps during 2007, while the opposite occurs at the end of the sample period.


                                                                                                                                                                                                              Figure 2
                                                                                      Interbank Rate - Monetary Policy Rate Spread
                                                                            Panel (a)                                                                                                                                               Panel (b)
       ir-mpr Spread: Banking System                                                                                                                                                                                        ir-mpr Spread: Level Bank
                                                                                                                                                                                                                    0.50
         0,50




         0,25                                                                                                                                                                                                       0.25




         0,00                                                                                                                                                                                                       0.00




        -0,25
                                                                                                                                                                                                                    -0.25




        -0,50
                                                                                                                                                                                                                    -0.50
                2006,06
                          2006,07
                                    2006,08
                                              2006,10
                                                        2006,11
                                                                  2007,01
                                                                            2007,02
                                                                                      2007,04
                                                                                                2007,05
                                                                                                          2007,07
                                                                                                                    2007,08
                                                                                                                              2007,10
                                                                                                                                        2007,11
                                                                                                                                                  2008,01
                                                                                                                                                            2008,02
                                                                                                                                                                      2008,03
                                                                                                                                                                                2008,05
                                                                                                                                                                                          2008,06
                                                                                                                                                                                                    2008,08




                                                                                                                                                                                                                            2006.06
                                                                                                                                                                                                                            2006.06
                                                                                                                                                                                                                            2006.07
                                                                                                                                                                                                                            2006.08
                                                                                                                                                                                                                            2006.09
                                                                                                                                                                                                                            2006.10
                                                                                                                                                                                                                            2006.11
                                                                                                                                                                                                                            2006.12
                                                                                                                                                                                                                            2007.01
                                                                                                                                                                                                                            2007.02
                                                                                                                                                                                                                            2007.03
                                                                                                                                                                                                                            2007.04
                                                                                                                                                                                                                            2007.05
                                                                                                                                                                                                                            2007.05
                                                                                                                                                                                                                            2007.06
                                                                                                                                                                                                                            2007.07
                                                                                                                                                                                                                            2007.08
                                                                                                                                                                                                                            2007.09
                                                                                                                                                                                                                            2007.10
                                                                                                                                                                                                                            2007.11
                                                                                                                                                                                                                            2007.12
                                                                                                                                                                                                                            2008.01
                                                                                                                                                                                                                            2008.02
                                                                                                                                                                                                                            2008.03
                                                                                                                                                                                                                            2008.04
                                                                                                                                                                                                                            2008.05
                                                                                                                                                                                                                            2008.05
                                                                                                                                                                                                                            2008.06
                                                                                                                                                                                                                            2008.07
                                                                                                                                                                                                                            2008.08
        Source: Authors’ calculations based on information provided by the Central Bank of Chile.



        In order to shed some light on this heterogeneity, Table 3 presents interbank
market information for large-, medium- and small-size banks.9 Three facts
emerge: a) the medium- and small-scale banks exhibit an asking ir
approximately two times larger than large banks -1.4 vs. 3.3 and 2.5 bps,
respectively;10 b) the larger-banks are willing to lend to a lower ir (2.8 bps)
than medium- (3.5 bps) and small-banks (4.0 bps); and c) the size of the loans
as percentage of assets is quite higher in small-scale banks (2.0%) than in large-

9
     These categories of banks are the most relevant in the Chilean banking system both in terms of assets and number.
More importantly, for our study, they explain more than 70% of the interbank market activity.
10
     One possible explanation for the lower asking ir of large-scale banks is that these banks are able to finance their
reserve needs at a lower cost. To verify if large banks have higher funding costs than medium-scale banks, we build a
measure of funding costs as the ratio of monthly interest payment to total liabilities of each bank relative to the average
banking system. Values higher than one of this measure reflect funding cost higher than the average. On the contrary,
values lower than one reflects cheaper funding cost than the banking system. The results show that large-scale bank are
able to obtain funding almost 1.2 percent cheaper than the average bank, while medium-scale banks have an average
funding cost 3.5 percent higher than the average.



                                                                                                                                                                                                                                                        8
and medium-size banks -0.2% and 0.6%, respectively. These findings suggest
that different class of banks participate in the interbank market for different
purposes, while larger tend to use the interbank market to drain liquidity, the
medium-scale participate to obtain liquidity.


                                                    Table 3
                                     Interbank Market Statistics
                                        June 2006-December 2007
                                                      Large-Scale   Medium-Scale     Small-Scale   Average Banking
                                                         Banks          Banks           Banks          System

Average Asking Spread (bps)                               1,4             3,3            2,5             2,9
Average Lending Spread (bps)                              2,8             3,5            4,0             2,9
Average daily Interbank Asking Volume*                    25,8           14,1            5,4            10,5
 % of Assets                                             0,2%            0,5%           2,0%            0,4%
 % of Financial Investment                               1,7%            6,4%           8,8%            3,4%
Average daily Interbank Loans Volume*                     37,4            9,7            4,7            10,5
 % of Assets                                             0,3%            0,4%           1,7%            0,4%
 % of Financial Investment                               2,5%            4,4%           7,6%            3,4%

    Source: Authors’ calculations based on information provided by the Central Bank of Chile.




3. Empirical Analysis
    In this section we present time series and panel estimations to disentangle
the main driving forces behind the dynamics of the ir, considering both global
and individual liquidity needs. A time series approach is useful to analyze the
role of aggregate shocks, while the panel estimation allows us to exploit the
heterogeneity of the ir across banks. Jointly, we will be able to study the
differential effect of shocks across different types of banks.


3.1.      Time Series Analysis
    From a time series perspective, modeling economic variables requires
evaluating if the series are stationary. Stationary variables and integrated series
demand completely different modeling strategies. As Table A in Appendix 2
shows, the ir and the mpr behave very persistently during the sample period. In
fact, the half-life of a shock on the ir is longer than one year, while the half-life
of the mpr is even more persistent. Part of these dynamics could be explained




                                                                                                                 9
by the discrete changes in the mpr. 11 However, in order to avoid the problem of
spurious results, it is necessary to test the existence of unit roots.12 We apply a
battery of unit-root tests to both series, including the traditional Augmented
Dickey-Fuller test, the Elliot et al. (1996) efficient test, denoted as DF-LS, and
the KPSS and Phillip-Perron tests. Results successively confirm for each of
these tests that it is not possible to reject the null hypothesis of a unit root for
ir and the mpr series.
       Since the ir and the mpr move closely together and sporadically deviate from
each other (see Figure 1, panel (a)), we evaluate the presence of a long-run
relationship between both series. Evaluating this hypothesis is equivalent to
testing whether the residual of an OLS regression between ir and mpr is non-
stationary against the alternative that it is stationary. Results reject the null of
unit-root for residuals, confirming the presence of a long run relationship.13 The
low value for the half-life of the ir-mpr spread (less than 2 trading days) seems
to confirm the stationary nature of this variable.
       Given the non-stationary behavior of the ir and its co-integration with the
mpr, the most natural approach is an error correction model (ECM) with the
mpr as the long term anchor.14 This approach is not novel in the literature. In
fact, it has been applied by Nautz and Offermanns (2006), and Sarno and
Thornton (2002) to model the EONIA in the Euro zone and the federal funds
rate in United States, respectively.
       The ECM we estimate is formulated as follows:


                   Δirt = α 0 ( irt −1 − mprt −1 ) + α1Δmprt −1 + α 2 Δirt −1 + δ ´ X + ε t ,                          (1)
where irt is the interbank rate, mprt                             the monetary policy rate, X other
explanatory variables, and Δ the first-difference operator. The parameter α 0 is
the rate at which the deviations of ir from the mpr are closed each day. The
vector of other explanatory variables, X, involves several monetary operations


11
     Testing for unit root in the mpr is challenging because this rate changes discretely and its increments are irregularly
spaced in time. An overwhelming majority of the literature fails to reject a unit root based on the low power of unit root
test when dealing with series that present infrequent changes (Hamilton and Jorda, 2002).
12
     In practice, both stationary and non-stationary modeling strategies for the mpr are considered in the literature. We
take one of the stands in the literature testing for the presence of unit root in the ir and the target rate.
13
     Table A, third column.
14
     It is worth mentioning that an error correction specification could also be obtained from a more general specification
where the ir is just modeled as a function of its own lags, lags from the mpr plus other controls.



                                                                                                                        10
variables,         regulatory capital              requirements, institutional                  investor       deposit
variables, mpr surprises, external variables and calendar effects.
       Regarding monetary operations, we consider discretionary operations that
provide liquidity (repos) and those that reduce it (liquidity deposits), and non
discretionary instruments (permanent credit facilities) expressed in net terms,
that is, liquidity injections minus drainage. It is worth mentioning that the
distinction between discretional and permanent monetary operations matters for
the analysis of the determinants of the ir. While the first group comprises of
agreements on an occasional basis issued at the mpr, the second one corresponds
to operations in which every bank is allowed to deposit (withdraw) at 25 bps
below (above) the mpr. From a policy standpoint, to determine the effectiveness
of discretional instruments is relevant for better fine-tuning in extraordinary
episodes of decoupling of the ir from the mpr and.
        Regulatory capital requirements are also included since they correspond to
indirect instruments used by the Central Bank to drain liquidity.15 Additionally,
we consider deposits in commercial banks by PF and by other investors (i.e.,
insurance companies, mutual funds, households, etc.). The inclusion of PF
deposits may be relevant because the share of its maintained deposits’ portfolio
in whole deposits of the system is above 20 percent and, therefore, could end up
influencing the ir.16 We divide PF deposits into short term and long term,
corresponding to less or more than 90 days respectively. Since there is no
information to classify the non-PF deposits by term, we only consider the
aggregates.
       Other domestic variables included are monthly mpr surprises, measured as
the difference between the effective mpr and the implicit expected rate in
forward contracts two weeks before the monetary policy meeting. We also
control for calendar effects through dummies extensively used in the literature:
day of monetary policy meeting –generally the second Thursday of each month-,
the day that banks must cover their reserve requirement –9th of each month-,
and the day of value-added tax payment.17 Finally, in order to capture the
international liquidity conditions, we consider external variables such as the

15
     In Chile, banks are obligued to deposit the difference between their current liabilities and the amount equivalent to
times and a half of their capital and reserves in an special account in the Central Bank.
16
     PF in Chile are important players in key asset prices. For instance, Cowan, Rappaport and Selaive (2006) provide
evidence of the role of PF on the exchange rate.
17
     For instance, Hamilton (1996), Sarno and Thornton (2002), and Nautz and Offermanns (2006).



                                                                                                                      11
CBOE Volatility Index (VIX) and the Libor-OIS spread. While the Libor -
Overnight interest swap spread capture the role of “liquidity contagion” coming
from external markets, the VIX captures market expectations of near-term
volatility.


3.1.1. Results
       The OLS estimations rely on the assumption that the independent variables
are predetermined or statistically exogenous. However, it is likely that monetary
operations could be endogenous to the dynamics of the ir. Central banks
respond to price signals when they decide the amount they will put in the
lending window in the form of repos. Similarly, when commercial banks choose
to obtain funds from the interbank market over the permanent facilities
alternative, they are implicitly responding to the relative cost of both sources of
liquidity. Finally, given that the ir represents the shortest end of the yield
curve, movements of this price could affect the amount of deposits in
commercial banks.
       Following the previous reasoning, a straightforward OLS estimation could
generate biased and inconsistent parameters. Thus, given the potential
endogeneity of the covariates, we run the Hausman (1978) test to all variables.
The test supports statistical exogeneity for all the variables with the exception
of net permanent facilities. Therefore, we use Instrumental Variables (IV)
procedure, choosing as external instruments for differences of net permanent
facilities their lagged levels, lagged values of the ir-mpr spread, daily dummies
and dummies for positive and negative values of the ir-mpr spread.18 A similar
approach using IV estimation has also been used recently by Cocco et al (2009).
       Table 4 presents our estimates for the short-run dynamics of the ir, which
include up to one lagged difference of the ir and the mpr. Several findings
deserve attention. First, the speed of convergence of the ir to the mpr is
relatively high (0.28-0.34, approximately) indicating that approximately one-
third of the gap between these two variables is reduced in one day. This
magnitude is a little higher but otherwise near to the estimates for the Euro
interbank market by Nautz and Offermanns (2006), who find a speed of
convergence of 0.26. Second, the short-run effect of changes in the mpr is


18
     The set of instruments includes lags of the endogenous variables and lags of the ir-mpr spread.



                                                                                                       12
significantly positive, but does not entail a one-for-one change in the ir. In fact,
the estimated coefficient in all the specifications lies in the range 0.15-0.22,
which suggests that the effect on the ir of a one-time change in the mpr is
distributed over time. This finding is also consistent with the evidence provided
by Nautz and Offermanns (2006), Angelini (2002) and Linzert and Schmidt
(2008).
       In Col [1] of Table 4 we test some calendar effects that could potentially
affect the liquidity position of the banks: the day of the monetary policy
meeting (which takes the value of one for contemporaneous and following day of
the meeting), the value-added tax payment day (which takes the value of one
on the day of payment and on the previous day) and the preceding four days to
the end of the maintenance period.19 In addition, we include a dummy that
takes the value of one in the first four days of the maintenance period in order
to control for the higher demand because of the banks’ obligation to comply
with at least 90% of the required reserve by the 23rd of each month. The aim of
this intermediate target is to encourage less volatility in the banks’ reserve
requirement compliance and thus the ir.
       Our results suggest that the ir does not vary significantly in the final days of
the maintenance period. On the contrary, our results show that in the days
prior to the VAT’s payoff day and on the days surrounding the monetary policy
meeting, the ir increases approximately 2 bps, although in the case of the
monetary policy meeting the increase is significant only in the three last
specifications. Similarly, in each of the first four days of the maintenance period,
the ir increases by 3 bps. This result is robust to different specifications of the
length of dummy variables, and as we show in columns [2] to [4] of Table 4,
they are also robust to the inclusion of alternative sets of control variables.




19
     Consistently with former theoretical models which consider monthly reserve requirements as the most important shock
affecting banks’ liquidity position (see Ho and Saunders, 1985; Freixas et al, 2000; Allen and Gale, 2000; King, 2004
among others), the end of maintenance period dummy variable is by far the most extensive calendar effect considered in
the literature. See Hamilton (1996); Perez and Quiros (2002); Wurtz (2003); Prati et al. (2003) and Nautz and
Offermanns (2006), among others.



                                                                                                                    13
                                                    Table 4
                                              IV Estimations
                                     Dependent Variable: Δirt
                                        May 2005 – Aug 2008
                                                          [1]                [2]          [3]          [4]

ir (t-1)                                               -0.342 ***         -0.299 ***   -0.295 ***   -0.286 ***
mpr (t-1)                                               0.343 ***          0.299 ***    0.295 ***    0.286 ***
Δ mpr                                                   0.215 **           0.179        0.175        0.142

Δ ir (t-1)                                             -0.092 ***          0.032        0.026        0.031

Δ mpr (t-1)                                             0.230 *            0.251 **     0.261 **     0.223 *

Calendar Effects
MP Meeting day                                          0.021               0.03 **     0.032 **     0.034 **
VAT Payoff day                                          0.026 **            0.02 *      0.018        0.015
Pre- End of Maintenance Period                         -0.006             -0.004       -0.003       -0.003
Post- End of Maintenance Period                         0.028 ***           0.03 ***    0.027 **     0.028 **

Central Bank's Open Market Operations

Δ Injections                                                              -0.057 ***   -0.061 ***   -0.062 ***
Δ Injections (t-1)                                                        -0.003       -0.007       -0.007
Δ Draining                                                                 0.014        0.011        0.007
Δ Draininng (t-1)                                                          0.056 **     0.054 **     0.059 **
Δ Mandatory Reserve Requirement                                            0.011        0.015        0.011
Δ Mandatory Reserve Requirement (t-1)                                      0.111 **     0.112 ***    0.116 ***
Δ Net Permanent Facilities                                                 0.102 *      0.103 *      0.111 **
Δ Net Permanent Facilities (t-1)                                          -0.091       -0.083       -0.095

                                                                          [0.055]      [0.057]      [0.058]

Private Investors Depositors

Δ Other Investors' Deposits                                                            -0.008       -0.004
Δ Other Investors' Deposits (t-1)                                                      -0.006       -0.004
Δ Short-Run Pension Funds Deposits                                                      0.091        0.093
Δ Short-Run Pension Funds Deposits (t-1)                                               -0.112 *     -0.123 *
Δ Long-Run Pension Funds Deposits                                                       0.110        0.118
Δ Long-Run Pension Funds Deposits (t-1)                                                -0.142 *     -0.141 *

Other External & Domestic Variables

Forward IR - MPR                                                                                    -0.043
Forward IR - MPR (t-1)                                                                              -0.030
Libor-Ois                                                                                            0.027
Libor-Ois (t-1)                                                                                     -0.022
VIX                                                                                                  0.017
VIX (t-1)                                                                                           -0.044
Observations                                              795                795          795          795
Note: * significant at 10%; ** significant at 5%; *** significant at 1%

  Source: Authors’ calculations.




                                                                                                                 14
             The estimates considering monetary operations are presented in the block
named “Central Bank’s Open Market Operations” in Cols. [2] to [4]. Both
contemporaneous and lagged discretionary injections and drainages have the
expected signs and similar magnitudes. The difference between injections and
drainages lies in the timing of impact. While injections are statistically
significant contemporaneously, drainages reach significance one period lagged
(both coeffcients are statistically significant at the 95% confidence level).20 The
estimated coefficients for these variables are robust along all the specifications
and, more importantly, they are economically significant. However, the size of
the average drainages and injection operations are quite different -$ 600 and $
300 billion, respectively (Table 2). Therefore, in practice, when the central bank
had operated through repos, the impact on the ir has been two times higher in
draining than injecting liquidity. In effect, if we employ the average (median)
size of each type of operation, the expected effect of drainages and injections on
the ir is 3.4 (3.1) and 1.7 (1.4) bps, respectively. These results suggest that
taking the ir to the mpr by the Central Bank is equally effective when the
market has liquidity shortage with respect to liquidity abundance in the
interbank system, but the average intervention implies that drainages are
economically more significant than liquidity injections.
             Regarding permanent monetary operations, we obtain a positive
contemporaneous effect, and a negative lagged effect of similar magnitude that
offset the initial positive effect on the ir. In fact, it is not possible to reject the
null hypothesis that the sum of both coefficients is statistically equal to zero at
usual confidence intervals. In other words, the estimates imply that “changes”
in the volume of the operations through permanent facilities do no affect
permanently the ir. However, this does not imply that existence of this
mechanism does not affect the dynamics of the ir. The reason behind this
clarification is that this instrument is available every day and, therefore, the
market could have internalized its operation in the valuation of the ir and,
therefore, the use (or not) of this facility is already incorporated in the ir.21
Finally, the lagged change in the reserve requirement—which is proportional to


20
     Hereafter we will refer to discretional injections and draining simply as “injections” and “draining”.
21
     To test formally if the existence of this mechanism affects the dynamics of the ir, we should have data covering a
period without the operation of the permanent facilities, which is not available. However, such analysis goes beyond the
purpose of this paper.



                                                                                                                    15
the capital of each bank—is strongly significant, suggesting that higher reserve
requirements reduce the liquidity of the banks and, therefore, increase the ir.
       In Cols. [3] and [4] we test the relevance of private deposit variables which
supposedly provide liquidity to the banking system. We test the effect of
deposits by splitting overall deposits into three categories: deposits by PF with
duration of up to 90 days (short-run deposits), deposits by PF with duration
longer than 90 days (long-run deposits) and deposits by other private investors.
The only statistically significant variables are the lagged short- and long-run PF
deposits.22 In order to evaluate the economic significance of long-run PF
deposits, we employ the average daily change of short- long-run PF deposits —
-$0.53 and $4.15 billion respectively—, leading to a potential effect on the ir
reaching -0.006 and 0.05 bps. This magnitude is quite low. However, the
potential effects of PF deposits could be quite important. In fact, if PF liquidate
25% of their short- and long-run deposits, the ir could go up by 30 bps (5.6 and
24.3 bps respectively).23
       The final variables set we consider consists of mpr surprises (proxied by the
forward ir – mpr spread) and two variables that capture the external
environment: the Libor-OIS spread and the VIX. Neither of these variables
prove to be statistical significant.
       In sum, we have two sets of candidates that correlate significantly with
changes of the ir: standard calendar effects and central bank’s open market
operations. In order to asses the relative statistical significance of those
variables, in Table 5 we test the null hypothesis that all the regressors within a
given variable set are non-significant for each specification. Results in the first
row of Table 5 show lagged levels and differences of ir and mpr being strongly
significant at the 1% level. Similarly, results in rows two and three confirm both
calendar effects and central bank’s operations being statistical significant at the
1% level. Rows four and five reveal that private investors deposit variables and
other external and domestic variables are both non-significant at standard
confidence levels. We also compute three additional measures for the fit of each
regression: the Akaike and the Bayesian Information Criterions (AIC and BIC,


22
     We also consider deposits by private investors’ variables overall deposits and overall PF deposits (both short- and
long-run). The results are qualitatively similar and are therefore not reported.
23
     Notice that this estimation assumes perfect linearity -constant coefficient-, which could be a conservative assumption
for this type of estimation.



                                                                                                                         16
respectively), and the regression’s adjusted R-Squared. AIC suggests that the
model including including monetary operations and private investors deposits as
preferred to specification 1 and 2, while BIC points to a specification only the
calendar effects better adjusts the data (specification 1). On the contrary,
specifications including other external variables (specifications 3 and 4,
respectively) are never preferred by AIC or BIC to the more parsimonious
specifications 1 and 2. Finally, the last row in Table 5 confirms that the
inclusion of monetary operations into the model improves the adjusted R-
Squared from 0.30 to 0.34, while the inclusion of further variables is unable to
improve significantly the fit of the regression.


                                                                    Table 5
                                                                 Wald Tests
                                                    Dependent Variable: Δirt
                                                       May 2005 – Aug 2008

                                                                             [1]           [2]          [3]          [4]

              Lagged Levels and Differences of ir and mpr                  105.97 ***    67.22 ***    68.02 ***    61.43 ***

              Calendar Effects                                              19.41 ***    19.59 ***    16.67 ***    16.98 ***

              Central Bank's Open Market Operations                                      70.32 ***    73.34 ***    70.38 ***

              Private Investors Depositors                                                             5.21         5.31

              Other External & Domestic Variables                                                                   1.59
              Observations                                                    795          795          795          795
              Akaike Information Criterion                                -2041.7       -2066.4      -2074.4      -2047.1
              Bayesian Information Criterion                              -1999.6       -1986.8      -1966.8      -1911.4
              R-squared                                                      0.30          0.34         0.35         0.34
              Note: * significant at 10%; ** significant at 5%; *** significant at 1%

Source: Authors’ calculations.



3.1.2.          Asymmetric Effects
        In this subsection we explore whether our estimates are sensitive to
aggregate market liquidity, i.e. to positive and negative values of the ir - mpr
spread. For such a purpose, we consider the specification excluding other
domestic and external variables (Col. [3], Table 4).24 Operationally, we estimate
a regression in which the speed of convergence, the contemporaneous and lagged
changes in the ir and in the mpr, discretional monetary operations and deposits


24
     The results are robust to different specifications of the ir dynamics.



                                                                                                                               17
variables are interacted with a dummy variable that takes the value one if the
spread is positive and 0 otherwise. In order to determine whether the
coefficients are statistically different in both cases, we compute Wald tests.
   Table 6 presents the coefficients for negative and positive spreads in Cols. [1]
and [2] respectively, while Col. [3] shows the statistics of the Wald test under
the null hypothesis of non-asymmetric coefficients –i.e., that the coefficients are
not statistically different. The results reveal asymmetric effects on just some of
the variables. The first source of asymmetry emerges from the lagged ir – mpr
spread, which is significantly higher when the market is illiquid than with a
liquid market (0.46 vs. 0.32). Secondly, results reveal the change in mpr being
also asymmetric. In fact, when the spread is positive, changes in the mpr are
translated into a one-to-one basis to the ir, but the pass-through is significantly
lower if the spread is negative (less than one-fifth). Finally, we also find some
evidence of asymmetries in mandatory reserves.
                                                              Table 6
                                     Testing Asymmetric Coefficients
                                                                          [1]                   [2]           [3]
                                                                    Illiquid Market         Liquid Market    Chi2
                                                                      ir > mpr               ir < mpr

           ir (t-1)                                                      0.462 ***             0.324 ***     [2.31]
           mpr (t-1)                                                    -0.455 ***             -0.329 ***    [2.80] *
           Δ mpr                                                         1.050 ***             0.130        [19.89] ***
           Δ ir (t-1)                                                   -0.086                 -0.067        [0.07]
           Δ mpr (t-1)                                                   0.488 ***             0.198         [1.43]

         Central Bank's Open Market Operations

           Δ Injections                                                 -0.041 ***             -0.070 **     [0.66]
           Δ Injections (t-1)                                           -0.017                 -0.068        [1.18]
           Δ Draining                                                   -0.024                 0.015         [2.00]
           Δ Draining (t-1)                                             -0.006                 -0.049        [3.25] *
           Δ Mandatory Bank Reserve Position                             0.027                 -0.050        [5.48] **
           Δ Mandatory Bank Reserve Position (t-1)                       0.067 **              -0.023        [8.52] ***

         Private Investors Depositors

           Δ Other Investors' Deposits                                  -0.025                 -0.078        [1.93]
           Δ Other Investors' Deposits (t-1)                            -0.022                 0.017         [0.76]
           Δ Short-Run PF Deposits                                       0.118                 0.175         [0.35]
           Δ Short-Run PF Deposits (t-1)                                -0.151 **              0.026         [0.09]
           Δ Long- Run PF Deposits                                       0.000                 0.068         [0.18]
           Δ Long- Run PF Deposits (t-1)                                 0.061                 0.023         [1.00]
         Observations                                                                 680
         Note: * significant at 10%; ** significant at 5%; *** significant at 1%

          Source: Authors’ calculations




                                                                                                                          18
3.1.3 Disentangling the Determinants of the ir: August 2007
       In this section, based on the fourth specification in Table 4 (Col. [4]), we
decompose the incidence of each one of the considered variables in the dynamics
of the ir at the end of August 2007. This exercise is relevant because during this
period the ir was systematically above the mpr—averaging 10.5 bps between
August 10th and September 12th, with a peak of 21 bps—(Figure 1) and,
additionally, it is not clear what were the main drivers behind this dynamic, i.e.,
PF deposits, international turmoil, expectations on the next monetary policy
meeting, etc.
            Figure 3 presents the performance of the model in terms of explaining the
ir (panel a) and, complementary, the contribution to the ir dynamics of the
different explanatory variables (panel b). In general terms, the model has a
relatively good performance at the beginning of August—recall that the model
has a daily frequency—but it does a poor job between the end of August and
the monetary policy meeting of September 13th. In particular, during the second
week of September, the explanatory variables are able to explain just a minor
part of the ir decoupling. In some sense, this behavior is consistent with the mix
of uncertainty associated with the response of monetary policy to both
inflationary pressures from the international financial turbulences that were
affecting the economy at that moment.
            With respect to the explained ir dynamics—and particularly at the
beginning of August— it is interesting to note that the calendar effects and
monetary operations have an active role in the behavior of the ir. The variance
decomposition indicates that the calendar effects, open market operations,
private deposits and other controls account for 40, 56, 4 and 1% of the
explained variance during the period under study, respectively. Moreover, the
maximum contribution of the open market operations in the August-September
episode is 11.1 bps when the difference between ir and mpr is close to 18 bps –
the fifth of September. As for PF, their role is restricted to just a couple of days
in mid-August that correspond to the loosening of the restrictions on PF to hold
foreign assets.25 In fact, the estimations indicate that the maximum PF
contribution to the ir occurred in the August episode, accounting for 2.9 bps of
the gap between the ir and the mpr in the period. This point contrasts with


25
     The limit to holding foreign assets was increased from 30% to 35% of total portfolio on August, 9th, 2007.




                                                                                                                  19
several opinions by market operators during those days regarding the impact on
the market liquidity conditions due to potential PF’ portfolio adjustments.26

                                                                     Figure 3
                                       Explaining the ir Dynamics: August 2007
                                    Panel (a)                                                                 Panel (b)
                   Explained versus Unexplained Share                                    Decomposition of Model’s Explained Share
                     Model                             Effective                              Monetary Operations         PF Deposits
     0.30                                                                       0.25          Calendar Effects            Other Deposits
                                                                                              Other Controls
                                                                                0.20
     0.20
                                                                                0.15
     0.10                                                                       0.10

                                                                                0.05
     0.00
                                                                                0.00
     -0.10
                                                                                -0.05

     -0.20                                                                      -0.10

             1/8     8/8     16/8      23/8     30/8       6/9     13/9                 1/8     8/8    16/8      23/8     30/8   6/9       13/9


Source: Authors’ calculations.

3.2.               Panel Data Analysis
               This section presents panel data estimates with the purpose of exploring
whether bank level differences could be relevant for explaining the dynamics of
the ir. Due to data availability, the sample period covers a shorter period than
in the previous section (from June 2006 to August 2008). The empirical model
estimated in this section is similar to the model used in the time series section.
In fact, we estimate a panel error correction model with IV to control for
endogeneity of some explanatory variables:27


                                     Δirit = α 0 ( irit −1 − mprt −1 ) + δ ' X i ,t + υi + ηt + ε it                                       (2)


where the dependent variable is defined as the change in the interbank asking
rate defined in section 2.1, and where υι and ητ correspond to fixed and time
effects, respectively,28 while the index i denotes each of the 29 banks in our
sample. Vector X contains the same controls used for time series estimations
with the only difference that they are disaggregated at the bank level. In
general, the notation for the other variables remains the same as before.

26
     See section 2.
27
     A quite similar econometric approach is performed by Cocco et al. (2009)
28
     We consider time effect with a weekly frequency. The reason behind this decision lies in the fact that the time
dimension (539) of our dataset is significantly higher than the number of individuals (29).



                                                                                                                                           20
         Similarly to time series estimations, we apply the Hausman (1978) test to
each covariate. The test supports the statistical exogeneity assumption for all
the variables except for net permanent facilities. For this variable, we consider
as external instruments the contemporaneous and lagged values of derivative
contracts. The logic behind the use of derivatives as instruments is that they
reduce the availability of banks to lend and borrow in the interbank market
because they employ part of pre-determined credit lines between banks to
operate between them, but the use of derivatives is not directly related to the ir
dynamics. Therefore, the use of derivatives is related to the endogenous
explanatory variable and, simultaneously, not to the error term.


3.2.1.    Baseline Estimations
         Table 7 presents the benchmark regressions. The main difference with
respect to time series estimations is the magnitude of the coefficients, which
tend to be higher in the panel dimension. Concretely, the speed of convergence
of the ir of each bank to the mpr is practically twice the speed at the
aggregated level, roughly 0.50 (Table 7) versus 0.29 (Table 4). On the other
hand, and perhaps more interestingly, the contemporaneous effect of injections
fluctuates around 0.58, while in the time series estimates are close to 0.05
(however, this coefficient has low statistical significance).
         Similarly, the magnitude of the drainage effect is 10 times the effect
estimated in the time series: 0.7 in panel estimations while in the time series it
is approximately 0.06. A similar situation occurs with the estimated effect of
injections, which is approximately three times higher than the estimated effect
in the time series dimension. With respect to calendar effects, they have similar
magnitudes compared to the time series estimates. The only difference is the
estimated effect for the monetary policy meeting dummy variable, which turns
out to be negative and significant, and the value-added payoff day dummy,
which turns out to be non-significant. The set of calendar effects also include a
dummy that takes the value one for those banks that are net lenders in each
trading day. We do this in order to capture the fact that lender banks have
probably more liquidity at hand and, therefore, should face a lower asking ir.
Our belief is confirmed by the finding of an ir 0.7 bps lower for those banks.
         The existence of higher impacts at individual than aggregated level
reflects the high heterogeneity across banks in terms of the use of instruments


                                                                                 21
and liquidity positions at each moment.29 In this sense, this result highlights the
importance of a monetary planning that takes into account the liquidity
position of each bank in order to maximize the efficiency of its instruments.
             To illustrate the implications of the magnitude of the individual
elasticities, if the Central Bank reduces liquidity by $ 700 billion through
liquidity deposits in 9 commercial banks,30 the ir of the banks using such
instrument will go up by 5.3 bps. In contrast, time series estimates indicate that
the aggregated ir will decrease by only 3.7 bps. In contrast, a liquidity injection
of 300 billion through repo operations in 5.1 commercial banks reduce the ir of
those banks in a similar amount than the estimated response in the time series
section.31
                                                             Table 7
                            Panel IV Estimation. Dependent Variable: Δirit
                                Sample Period: June 2006 to August 2008
                                                                           [ 1 ]            [ 2 ]           [ 3 ]

                 ir (t-1) - mpr (t-1)                                    -0.542 ***      -0.481 ***      -0.479 ***

                 Δ mpr                                                    0.228 ***       0.436 ***       0.437 ***

                 Δ ir (t-1)                                              -0.058 ***      -0.058 **       -0.059 **

                 Δ mpr (t-1)                                              0.161 ***       0.417 ***       0.417 ***

                 Calendar Effects

                 MP Meeting day                                         -0.010     *     -0.018 ***      -0.017 ***

                 VAT Payoff day                                         -0.004           -0.001          -0.001

                 Pre- End of Maintenance Period                         -0.009     ***   -0.007 *        -0.007 *

                 Post- End of Maintenance Period                        0.026      ***    0.027 ***       0.027 ***

                 Dummy Lender Bank                                      -0.006     **    -0.007 **       -0.007 **

                 Central Bank's Open Market Operations

                 Δ Injections                                                            -0.184 **       -0.181 **

                 Δ Injections (t-1)                                                        0.13           0.135

                 Δ Drainage                                                               0.725 **        0.702 **

                 Δ Drainage (t-1)                                                         0.679           0.649

                 Δ Net Permanent Facilities                                              -0.541          -0.529

                 Δ Net Permanent Facilities (t-1)                                         0.151           0.219
                 Private Investors Depositors

                 Δ Overall PFs Deposits                                                                  -0.095

                 Δ Overall PFs Deposits (t-1)                                                            -0.294

                 Δ Other Deposits                                                                         0.005

                 Δ Other Deposits (t-1)                                                                   0.059

                 Observations                                           3804               3085            3085

                 Groups                                                   22                  20              20
                 Robust standard errors in brackets; * significant at 10%; ** significant at 5%; *** significant at
                 1%. Estimations include individual and monthly fixed effects.

                     Source: Authors’ calculations.



29
     If banks were not heterogeneous, the aggregate elasticity will collapse to the individual estimates.
30
     The average liquidity deposit implies that 9.5 banks use this facility, each one requesting 73.1 billions pesos.
31
     The average repo operations implies that 5.1 banks use this facility, each one requesting 61.7 billions pesos.



                                                                                                                        22
3.2.2.         Asymmetric Response
          In this section we explore whether the asymmetric effects of monetary
operations and deposits on the ir dynamics found in time series analysis are also
valid on the ir of individual banks. Table 8 reports the coefficients for these
variables depending on the sign of the ir – mpr spread of each bank—i.e., liquid
and illiquid market. The results are similar to the aggregated estimates, but
they also add some new pieces of information with respect to the interbank
market dynamics.


                                                           Table 8
                                                 Testing Asymmetry
                                            Dependent Variable: Δirit
                               Sample Period: June 2006 to August 2008
                                                            [1]                       [2]                       [3]

                                                     Illiquid Market            Liquid Market

                                                        ir > mpr                  ir < mpr                      Chi2

ir (t-1) - mpr (t-1)                                              -0.547 ***                -0.450 ***                [207.4] ***

Δ mpr                                                             0.982 ***                  0.074 *                  [127.1] ***

Δ ir (t-1)                                                        0.001                     -0.106 ***                 [4.90] **

Δ mpr (t-1)                                                       0.083                      0.163 *                   [4.52] **

Central Bank's Open Market Operations

Δ Injections                                                      -0.096                     0.000                     [0.19]

Δ Injections (t-1)                                                0.125                     -0.119                     [0.00]

Δ Drainage                                                        0.088                      0.765 ***                 [2.97] *

Δ Drainage (t-1)                                                  0.065                      1.709 ***                 [4.93] **

Private Investors Depositors

Δ Overall PFs Deposits                                            0.039                      0.400                     [0.62]

Δ Overall PFs Deposits (t-1)                                      -0.442                    -0.380                     [1.55]

Δ Other Deposits                                                  0.067                     -0.267                     [0.91]

Δ Other Deposits (t-1)                                            0.120 **                  -0.139                     [0.01]

Observations                                                                              3059

Groups                                                                                      20

Notes: Robust standard errors in brackets; * significant at 10%; ** significant at 5%; *** significant at 1%. Estimations include
individual and monthly fixed effects. The equations include the same controls used in the time series IV estimation

Source: Authors’ calculations.




                                                                                                                                   23
First, the speed of convergence is statistically higher when the banks are illiquid
or, equivalently, the banks’ capacity to bring down the ir is higher when its ir is
above the mpr. Moreover, and in line with time series estimations, the ir
adjustment to changes in the mpr is statistically higher when the ir is above
than below the mpr. In some sense, these results can be summarized as a higher
bank         capacity        to     adjust       to    an     illiquid      status—i.e.,          ir>mpr—and/or,
complementary, the mpr tends to be the relevant marginal rate for illiquid
banks, which is consistent with an ir higher than mpr, and vice versa.
            Regarding monetary operations, we find that discretionary drainages are
more effective when the market is liquid. In fact, the magnitude of the sum of
both contemporaneous and lagged draining coefficients when the market is
liquid is almost ten times the coefficients when the market is illiquid. On the
other hand, injections are not statistical significant. The same is true for PFs
overall deposits, and for the contemporaneous value of depostis by other
investors.


3.2.3 Large and Medium Banks
            In this subsection we evaluate if the responsiveness of the ir depends on
the bank’s scale. For such purposes, and following the bank classification
proposed by Jara and Oda (2007), we run a different regression for the large-,
medium-, and small-banks. These authors make a cluster analysis for the
Chilean banking industry, defining each cluster according to the Euclidean
distance of each bank with respect to others which is dependent of a set of
characteristics.32
            Results in Table 8 reveal that large-scale banks are able to adjust faster
to misalignments of the ir from the mpr. In addition, large-scale banks are less
responsive to variations of the mpr. These results are consistent with the fact
that large-sized banks have a bigger quantity of funding sources as well as
greater assets. On the other extreme, small-scale banks shows the smaller
coefficient of convergence and are more responsive to changes in the mpr.
            The main result, however, corresponds to the strong asymmetry observed
in the monetary operations depending on bank type. Open market operations
are non-significant for large- and medium-scale banks. This finding is consistent

32
     Jara and Oda (2007) consider the following characteristics: market share, leverage, degree of portfolio diversification
and target market.



                                                                                                                        24
with a higher degree of autonomy in the funding of this type of banks (see
section 2.3). On the contrary, small-scale banks are the most responsive
classification to open market operations. Actually, they are the only group
responding significantly to both liquidity and draining operations.




                                                           Table 9
                                  Panel IV Estimation by Type of Bank
                                            Dependent Variable: Δirit
                               Sample Period: June 2006 to August 2008
                                                          Large Banks              Medium Banks                Small Banks
                                                               [1]                       [2]                          [3]

  ir (t-1) - mpr (t-1)                                           -0.649 ***                  -0.55 ***                 -0.486 ***
  Δ mpr                                                           0.134                      0.197 ***                  0.299 ***
  Δ ir (t-1)                                                      0.002                     -0.047                     -0.083 ***
  Δ mpr (t-1)                                                     0.185                        0.08                         0.21 **
Central Bank's Open Market Operations
  Δ Injections                                                   -0.025                     -0.163                     -0.266 *
  Δ Injections (t-1)                                              0.074                      0.139                      0.212 *
  Δ Drainage                                                      0.294                      0.687                          1.36 ***
  Δ Drainage (t-1)                                               -0.439                      0.239                      0.986
Private Investors Depositors

  Δ Overall PFs Deposits                                         -0.224                      0.338                      0.932
  Δ Overall PFs Deposits (t-1)                                   -0.347                     -0.233                     -0.189
  Δ Other Deposits                                               -0.053                      0.042                      0.173
  Δ Other Deposits (t-1)                                          0.049                      0.012                      0.047
Observations                                                          497                      1650                         1395

Groups                                                                  4                         9                            7


Notes: Robust standard errors in brackets; * significant at 10%; ** significant at 5%; *** significant at 1%. Estimations include
individual and monthly fixed effects. The equations include the same controls used in the time series IV estimation

Source: Authors` calculations.




4. Conclusions
          In this paper we make use of three detailed micro-datasets to understand
the determinants of the dynamics of the ir in Chile, which allows us to evaluate
in detail the role of open market operations and private deposits. Regarding
monetary policy, we consider discretionary operations that provide liquidity
(repos) and those that reduce it (liquidity deposits), and non-discretionary


                                                                                                                                   25
instruments (permanent credit facilities). Also, the estimations control for
calendar effects, which are quite relevant in explaining the dynamics of the ir.
        In general terms, the main findings show the effectiveness of open market
operations in terms to get the ir closer to the mpr. This is especially valid to
discretionary operations. In fact, the point estimates of the coefficients related
to drainages and injections are statistically and economically significant. Indeed,
the average draining operation increases the ir approximately 3.4 bps, while the
opposite operation reduces the ir around 1.7 bps. The asymmetries detected
suggest that such effectiveness depends on the liquidity status at market level.
Specifically, open market operations seem to be more effective when the market
is illiquid –i.e., ir>mpr. Moreover, in this line of results, the estimates suggest
that the pass trough from mpr to ir is close to 1 when the ir is above the mpr.
Conversely, if the ir is below the mpr, the coefficient of pass trough is near to
0.15.
        The role of asymmetries of monetary operations is reinforced by the panel
estimates. In general, the panel’s point estimates of open market operations are
significant higher than the time series estimates –for instance, the magnitude of
the drainage effect is also 10 times the effect estimated in the time series– which
indicates that the effectiveness and access to central bank’s instruments is quite
heterogeneous across banks. The estimates by category of bank -large and
medium- show that part of this heterogeneity is captured trough this
classification, where the open market operations are less relevant to large banks
(the more liquid ones), and more relevant for small-sized banks.
        The results on PF deposits indicate that they are statistically significant
with a relative high coefficient –specially, long-run deposits- but if we consider
the behavior of this variable during the sample period, their economic relevance
is limited. In fact, the statistical tests oriented to evaluate the relevance of
potential explanatory variables suggest that bank’s deposits do not significantly
help to improve the econometric specifications of the ir. Traditional information
criteria statistics tilt towards a specification based on calendar effects and open
market operations as controls. Nonetheless, from a financial stability
perspective, the PF deposits could be quite relevant on the dynamics of the ir,
because PF accounts for approximately 20% of total bank deposits. In other
words, even though the PF’s deposits did not play an important role on the
dynamics of the ir during the sample period, if these investors rebalance their


                                                                                   26
portfolios abruptly against banks’ deposits, the effects on the interbank market
could have a systemic impact.
      Finally, the calendar effects are both statistical and economic significant.
For instance, the day of payment of the value-added-tax is associated with an
increase of the ir equal to 2 bps. This kind of result is relatively standard in the
literature, and even though market practitioners could be habituated to them,
they are puzzling. On one hand, these calendar effects are totally predictable -
for instance, they are not doubts about when the taxes are paid- and, if we
assume perfect markets, the ir should internalize such effects on its pricing. This
line of reasoning opens important questions about the frictions that could be
behind the calendar effects’ incidence.


References
Allen, F. and D. Gale (2000). “Asset Price Bubbles and Monetary Policy.”
     Working Papers 01-26, Center for Financial Institutions, Wharton School
     Center for Financial Institutions, University of Pennsylvania.
Angenili, P. (2002). “Liquidity Announcement Effects in the Euro Area.” Paper
     451, Banca D`Italia.
Balduzzi, P., G. Bertola, and S. Foresi (1997). “A Model of Target Changes and
     the Term Structure of Interest Rates.” Journal of Monetary Economics 39,
     223-49.
Bartolini, L., B. Giusepe, and A. Prati (2002). “Day-to-Day Monetary Policy
     and the Volatility of the Federal Funds Interest Rate.” Journal of Money,
     Credit and Banking 34, 137-159.
Balduzzi, P., G. Bertola, S. Foresi, and L. Klapper (1998). “Interest Rate
     Targeting and the Dynamics of Short-term Rates.” Journal of Money,
     Credit, and Banking 30, 26-50.
Cocco J., F. Gomes, and N. Martins (2009). “Lending Relationships in the
     Interbank Market.” Journal of Financial Intermediation 18, 24-48.
Cowan, K. D. Rappaport and J. Selaive (2006). “High Frequency Dynamics of
     the Nominal Exchange Rate in Chile.” Working Paper 433, Central Bank
     of Chile.
Elliott, G., T. Rothenberg, and J. Stock (1996). “Efficient tests for an
     autoregressive unit root.” Econometrica 64, 813-836.



                                                                                 27
Freixas, X. B. Parigi and J-C. Rochet (2000). “Systematic Risk, Interbank
     Relations, and Liquidity Provisions by The Central Bank.” Journal of
     Money, Credit and Banking 32(3), 611-638
Gaspar, V. G. Quiroz and H. Medizabal (2004). “Interest Rate Determination in
     the Interbank Market.” Working Paper 351. European Central Bank.
Hamilton J. (1996). “The Daily Market for Fed Funds”. Journal of Political
     Economy, 26-56.
Hamilton, J. and O. Jorda (2002). “A Model For The Federal Fund Target”
     Department of Economics 99-07, California Davis - Department of
     Economics.
Hausmann, J. A. (1978). “Specification Tests in Econometrics.” Econometrica
     46, 1251 - 1271
Ho, T. and A. Saunders (1985). “A Micro Model of the Federal Funds Market.”
     The Journal of Finance 3, 977-988.
Jara A. and D. Oda (2007). “¿Cómo Agrupar Las Instituciones Bancarias?: Un
     Aplicación de Análisis de Clusters.” Informe de Estabilidad Financiera,
     Primer Semestre 2007, Banco Central de Chile.
King, T. (2004). “Discipline and Liquidity in the Market for Federal Funds.”
    Working Paper 2003-02, Federal Reserve Bank of St. Louis.
Linzert and Schmidt (2008). “What Explains the Spread Between the Euro
     Overnight Spread and the ECB´s Policy Rate?”. Working Paper 983,
     European Central Bank.
Nautz D. and C. Offermanns (2006). “The Dynamics Relationship between the
     Euro Overnight Rate, the ECB’s Policy Rate and the Term Spread.”
     Discussion Paper, Series 1: Economic Studies, 01/2006. Deutsche
     Bundesbank.
Prati A., L. Bartolini and G. Bertola (2003). “The Overnight Interbank Market:
     Evidence from G-7 and the Euro Zone.” Journal of Banking and Finance,
     27, 2045-2083.
Raddatz, C. and S. Schmukler (2008). “Pension Funds and Capital Market
    Development: How Much Bang for the Buck?” Manuscript, World Bank.
Sarno L. and D. Thornton (2002). “The Dynamics relationship Between the
     Federal Funds Rate and the Treasury Bill Rate: An Empirical
     Investigation.” Working Paper, 2000-032C. Federal Reserve Bank of St.
     Louis.


                                                                           28
Spindt, P., and R. J. Hofmeister (1988). “The Micromechanics of the Federal
     Funds Market: Implications for Day-of-the-Week Effects in Funds Rate
     Variability.” Journal of Financial and Quantitative Analysis 23(4), 401-
     416.
Taylor, J. and J. Williams (2008). “A Black Swan in the Money Market.”
     Manuscript.



Appendix 1: Managing the ir in Chile

       The Central Bank applies its monetary policy through the definition of a
target level for the interbank rate (ir) known as the monetary policy rate (mpr).
To ensure that the ir remains close to the mpr, the Central Bank must regulate
the financial system’s liquidity (or reserves) through the use of several
instruments: open market transactions, buying and selling of short-term
promissory notes, lines of credit and liquidity deposits.
       Open market transactions are essentially carried out through regular
auctions of promissory notes issued by the Central Bank: short-term nominal
discount promissory notes (PDBC), and nominal and indexed promissory notes
(BCP and BCU). Banks, financial institutions administering PF, insurance
companies and mutual funds can participate in these tenders’ auctions. The
bidding of promissory notes is carried out using the single price per auction
method, that is, a cut-off rate is applied to all participants in the auction
placing winning bids, in what is known as the “Dutch method”. This encourages
competition among auction participants and tends to reflect current market
conditions more accurately.
       In the case of the (average) ir deviates from the policy rate due, for
instance as a result of liquidity levels below demand from the banking system,
liquidity is injected to lower the ir rate and bring it closer to the mpr. This
liquidity injection is generally achieved by overnight purchases of notes with
repurchase clauses (repos). When the opposite occurs, and there is excess
liquidity and the ir tends to be below the mpr, the excess is withdrawn by
selling short term promissory notes.
       Additionally, starting on January 2005, the Central Bank implemented
permanent credit (deposit) facilities which are intended to avoid the ir surpasses



                                                                               29
(be below) the mpr by more (less) than 25 basis points. In this context, the
implementation of open market operations followed common practices of
developed economies’ central banks (US, Canada, Europe, among many others).
       The Central Bank uses permanent liquidity credit lines to provide
financial institutions with overnight loans. This account requires collateral,
instruments authorized in the Compendium of Financial Norms. It does not
have quantitative limits, except for the availability of collateral of the applicant.
Currently, the received interest rate is set at 25 basis points above the mpr.
       Similarly, permanent liquidity deposits allow financial institutions to
deposit temporary excess liquidity overnight with the Central Bank and receive
a minimum return. Currently, this rate is set at 25 basis points below the mpr
and in practice this constitutes the floor of the ir.
       In order to regulate adequately financial system liquidity, the Central
Bank develops a cash flow program around the reserve requirement time period,
that is, from day nine of each month though day eight of the following month.
To encourage less volatility in the banks’ reserve requirement compliance and
thus the ir, there is also an intermediate reserve requirement on day 23 of each
month, the deadline by which the banks must have complied with at least 90%
of the required reserve.
       To program cash flow, projections are made for both supply and demand
of bank reserves that is bills and coins in the power of banks and balances in
banks’ current accounts in the Central Bank. Demand is of a derived nature
that basically depends on reserve requirement rates and trends forecast for
demand and term deposits, along with the behavior of currency in the public’s
hands. The supply of bank reserves depends on the behavior of currency in the
public’s hands and from the main sources of emission, particularly the
maturities   of   previously   auctioned   promissory    notes   and   other,   more
autonomous sources of monetary expansion for which projections are required.
These operations include eventual purchases or sales of dollars within the
financial system by the Central Bank and State financial operations having
monetary effects.
       Once the supply and demand for bank reserves have been determined,
the amount of notes to be tendered by the Central Bank is established. The
calendar of auctions is published the day before each new reserve period begins.
The liquidity projection for the next four weeks is monitored daily to permit


                                                                                  30
fine tuning operations on bank reserves, as needed, using the repo operations
already mentioned or special sales of short-term promissory notes. Worth to
mention that the mechanism to provide and dried out liquidity from banks
described above is quite similar -with particularities in the implementation that
may be crucial in the modeling strategy- in other economies.


Appendix 2: Unit Root Test

                                                     Table A1
                      Persistence, Unit Root and Co-integration Tests

                                                                     Interbank
                                          Target rate                   Rate                    Residual

Half-Life                                Not Defined                       345.2                        1.3

Unit-Root-tests

  Augmented Dickey - Fuller                     -0.314                    -0.409                     -4.733     ***

  Phillips - Perron (Zt)                        -0.379                    -0.863                   -11.306      ***

  DF - GLS                                       1.675                       0.31                    -3.993     ***

  KPSS                                              7.95   ***               8.15    ***             0.884      ***

 Note: Except for KPSS, all the tests have as null hypothesis the non-stationarity of the series. * significant at
 10%; ** significant at 5%; *** significant at 1%




                                                                                                                      31
Appendix 3: OLS Estimation (Baseline Time-Series Model)
                                            Table A2
                                         OLS Estimations
                                     Dependent Variable: Δirt
                                      May 2005 – Aug 2008
                                               [1]            [2]           [3]           [4]

  ir (t-1)                                    -0.343 ***   -0.285 ***    -0.281 ***    -0.272 ***
                                             [0.040]       [0.044]       [0.044]       [0.040]
  mpr (t-1)                                   0.343 ***     0.285 ***     0.281 ***     0.271 **
                                             [0.041]       [0.045]       [0.044]       [0.040]
  Δ mpr                                       0.217 **      0.158         0.154         0.134
                                             [0.099]       [0.107]       [0.109]       [0.115]
  Δ ir (t-1)                                  -0.094 ***   -0.066 *      -0.065 *      -0.084 *
                                             [0.035]       [0.037]       [0.037]       [0.036]
  Δ mpr (t-1)                                  0.232 *       0.268 *       0.277 *       0.233
                                             [0.129]       [0.142]       [0.146]       [0.149]

  Calendar Effects
  MP Meeting day                              0.021         0.031 **      0.032 **      0.033 **
                                             [0.014]       [0.014]       [0.014]       [0.014]
  VAT Payoff day                              0.025 **      0.025 **      0.023 **      0.021 *
                                             [0.011]       [0.011]       [0.011]       [0.012]
  Pre- End of Maintenance Period              -0.007       -0.007        -0.005        -0.005
                                             [0.006]       [0.006]       [0.006]       [0.006]
  Post- End of Maintenance Period             0.027 ***     0.015 *       0.012         0.013
                                             [0.009]       [0.008]       [0.009]       [0.009]

  Central Bank's Open Market Operations
  Δ Injections                                              -0.054 ***    -0.058 ***    -0.057 ***
                                                           [0.015]       [0.015]       [0.015]
  Δ Injections (t-1)                                        -0.005        -0.010        -0.011
                                                           [0.014]       [0.014]       [0.014]
  Δ Draining                                                 0.017         0.014         0.013
                                                           [0.014]       [0.014]       [0.014]
  Δ Draininng (t-1)                                          0.006         0.006         0.005
                                                           [0.013]       [0.012]       [0.012]
  Δ Mandatory Reserve Requirement                            0.014         0.017         0.018
                                                           [0.020]       [0.019]       [0.019]
  Δ Mandatory Reserve Requirement (t-1)                      0.063 ***     0.067 ***     0.067 ***
                                                           [0.019]       [0.019]       [0.019]
  Δ Net Permanent Facilities                                 0.110 ***     0.112 ***     0.113 ***
                                                           [0.018]       [0.018]       [0.017]
  Δ Net Permanent Facilities (t-1)                           0.033 *       0.033 *       0.036 **
                                                           [0.018]       [0.018]       [0.017]




                                                                                                     32
                                            Table A2 (cont.)
                                            OLS Estimations
                                      Dependent Variable: Δirt
                                        May 2005 – Aug 2008

                                                       [1]             [2]       [3]          [4]

Private Investors Depositors
Δ Other Investors' Deposits                                                    -0.018       -0.014
                                                                              [0.019]      [0.019]
Δ Other Investors' Deposits (t-1)                                              -0.007       -0.005
                                                                              [0.015]      [0.015]
Δ Short-Run Pension Funds Deposits                                             0.089        0.084
                                                                              [0.067]      [0.067]
Δ Short-Run Pension Funds Deposits (t-1)                                       -0.051       -0.057
                                                                              [0.051]      [0.051]
Δ Long-Run Pension Funds Deposits                                              0.107        0.109
                                                                              [0.081]      [0.080]
Δ Long-Run Pension Funds Deposits (t-1)                                        -0.125 **    -0.119 *
                                                                              [0.062]      [0.062]
Other External & Domestic Variables
Forward IR - MPR                                                                            -0.016
                                                                                           [0.052]
Forward IR - MPR (t-1)                                                                      -0.067
                                                                                           [0.056]
Libor-Ois                                                                                   0.087
                                                                                           [0.160]
Libor-Ois (t-1)                                                                             -0.108
                                                                                           [0.149]
VIX                                                                                          0.001
                                                                                           [0.052]
VIX (t-1)                                                                                    0.009
                                                                                           [0.052]
Observations                                            804            804       804          804
Akaike Information Criterion                       -2068.3          -2184.6   -2181.6      -2178.5

Bayesian Information Criterion                     -2021.4          -2100.2   -2069.1      -2037.8
R-squared                                                0.3           0.41      0.42         0.42

Robust standard errors in brackets

* significant at 10%; ** significant at 5%; *** significant at 1%




                                                                                                       33
Appendix 4: Full Tables
                                 Table A3 (Extended Table 4)
                              IV Estimations; Dependent Variable:       Δirt
                                Sample Period: May 2005 – Aug 2008


                                                 [1]           [2]                [3]           [4]

 ir (t-1)                                      -0.342 ***   -0.299 ***         -0.295 ***    -0.286 ***
                                               [0.041]      [0.045]            [0.043]       [0.042]
 mpr (t-1)                                      0.343 ***    0.299 ***          0.295 ***     0.286 ***
                                               [0.041]      [0.045]            [0.043]       [0.043]
 Δ mpr                                          0.215 **     0.179              0.175         0.142
                                               [0.099]      [0.109]            [0.109]       [0.116]
 Δ ir (t-1)                                    -0.092 ***    0.032              0.026         0.031
                                               [0.035]      [0.065]            [0.067]       [0.069]
 Δ mpr (t-1)                                     0.230 *      0.251 **           0.261 **      0.223 *
                                               [0.129]      [0.119]            [0.123]       [0.127]

 Calendar Effects
 MP Meeting day                                 0.021         0.03 **           0.032 **      0.034 **
                                               [0.014]      [0.015]            [0.015]       [0.015]
 VAT Payoff day                                 0.026 **      0.02 *            0.018         0.015
                                               [0.012]      [0.012]            [0.012]       [0.013]
 Pre- End of Maintenance Period                -0.006       -0.004             -0.003        -0.003
                                               [0.006]      [0.006]            [0.006]       [0.006]
 Post- End of Maintenance Period                0.028 ***     0.03 ***          0.027 **      0.028 **
                                               [0.009]      [0.011]            [0.011]       [0.011]

 Central Bank's Open Market Operations
 Δ Injections                                                -0.057 ***         -0.061 ***    -0.062 ***
                                                            [0.017]            [0.017]       [0.017]
 Δ Injections (t-1)                                          -0.003             -0.007        -0.007
                                                            [0.014]            [0.014]       [0.014]
 Δ Draining                                                   0.014              0.011         0.007
                                                            [0.030]            [0.031]       [0.031]
 Δ Draininng (t-1)                                            0.056 **           0.054 **      0.059 **
                                                            [0.026]            [0.026]       [0.026]
 Δ Mandatory Reserve Requirement                              0.011              0.015         0.011
                                                            [0.030]            [0.029]       [0.029]
 Δ Mandatory Reserve Requirement (t-1)                        0.111 **           0.112 ***     0.116 ***
                                                            [0.028]            [0.028]       [0.028]
 Δ Net Permanent Facilities                                   0.102 *            0.103 *       0.111 **
                                                            [0.058]            [0.057]       [0.056]
 Δ Net Permanent Facilities (t-1)                            -0.091             -0.083        -0.095
                                                            [0.055]            [0.057]       [0.058]




                                                                                                           34
                                             Table A3 (cont.)
                               IV Estimations; Dependent Variable:              Δirt
                                  Sample Period: May 2005 – Aug 2008


                                                         [1]             [2]              [3]                [4]

Private Investors Depositors
Δ Other Investors' Deposits                                                             -0.008          -0.004
                                                                                       [0.020]         [0.020]
Δ Other Investors' Deposits (t-1)                                                       -0.006          -0.004
                                                                                       [0.017]         [0.017]
Δ Short-Run Pension Funds Deposits                                                      0.091            0.093
                                                                                       [0.078]         [0.078]
Δ Short-Run Pension Funds Deposits (t-1)                                                -0.112 *        -0.123 *
                                                                                       [0.068]         [0.069]
Δ Long-Run Pension Funds Deposits                                                       0.110            0.118
                                                                                       [0.088]         [0.089]
Δ Long-Run Pension Funds Deposits (t-1)                                                 -0.142 *        -0.141 *
                                                                                       [0.079]         [0.080]
Other External & Domestic Variables
Forward IR - MPR                                                                                        -0.043
                                                                                                       [0.048]
Forward IR - MPR (t-1)                                                                                  -0.030
                                                                                                       [0.042]
Libor-Ois                                                                                                0.027
                                                                                                       [0.058]
Libor-Ois (t-1)                                                                                         -0.022
                                                                                                       [0.059]
VIX                                                                                                      0.017
                                                                                                       [0.181]
VIX (t-1)                                                                                               -0.044

                                                                                                       [0.177]
Observations                                              795            795              795                795
Akaike Information Criterion                          -2037.7        -2069.4           -2062.9        -2055.6

Bayesian Information Criterion                        -1991.0        -1985.4           -1950.9        -1915.6
R-squared                                                 0.33           0.37             0.37               0.37

Note: Robust standard error in brackets. * significant at 10%; ** significant at 5%; *** significant at 1%




                                                                                                                    35
                                      Table A4 (Extended Table 6)
                                   Testing Asymmetric Coefficients
               Dependent Variable:          Δirit ; Sample Period: June 2006 to August 2008
                                                                 [1]                    [2]          [3]
                                                           Illiquid Market         Liquid Market
                                                             ir > mpr               ir < mpr        Chi2
  ir (t-1)                                                      0.462 ***              0.324 ***    [2.31]
                                                               [0.074]             [0.063]***
  mpr (t-1)                                                    -0.455 ***             -0.329 ***    [2.80] *
                                                               [0.073]             [0.064]***
  Δ mpr                                                         1.050 ***              0.130       [19.89] ***
                                                               [0.191]                [0.093]
  Δ ir (t-1)                                                   -0.086                 -0.067        [0.07]
                                                               [0.075]                [0.083]
  Δ mpr (t-1)                                                   0.488 ***              0.198        [1.43]
                                                               [0.142]                [0.191]
Central Bank's Open Market Operations
  Δ Injections                                                 -0.041 ***             -0.070 **     [0.66]
                                                               [0.014]              [0.035]**
  Δ Injections (t-1)                                           -0.017                 -0.068        [1.18]
                                                               [0.015]                [0.048]
  Δ Draining                                                   -0.024                  0.015        [2.00]
                                                               [0.028]                [0.031]
  Δ Draining (t-1)                                             -0.006                 -0.049        [3.25] *
                                                               [0.026]                [0.032]
  Δ Mandatory Bank Reserve Position                             0.027                 -0.050        [5.48] **
                                                               [0.028]                [0.034]
  Δ Mandatory Bank Reserve Position (t-1)                       0.067 **              -0.023        [8.52] ***
                                                               [0.028]                [0.035]
Private Investors Depositors
  Δ Other Investors' Deposits                                  -0.025                 -0.078        [1.93]
                                                               [0.019]              [0.034]**
  Δ Other Investors' Deposits (t-1)                            -0.022                  0.017        [0.76]
                                                               [0.017]                [0.042]
  Δ Short-Run PF Deposits                                       0.118                  0.175        [0.35]
                                                               [0.078]                [0.106]
  Δ Short-Run PF Deposits (t-1)                                -0.151 **               0.026        [0.09]
                                                               [0.068]                [0.148]
  Δ Long- Run PF Deposits                                       0.000                  0.068        [0.18]
                                                               [0.068]                [0.102]
  Δ Long- Run PF Deposits (t-1)                                 0.061                  0.023        [1.00]
                                                               [0.065]                [0.119]
Observations                                                                 680
Note: * significant at 10%; ** significant at 5%; *** significant at 1%




                                                                                                                 36
                         Table A5 (Extended Table 7)
               Panel IV Estimation, Dependent Variable:                       Δirit
                     Sample Period: June 2006 to August 2008
                                                          [1]             [2]              [3]
ir (t-1) - mpr (t-1)                                    -0.542 ***      -0.481 ***      -0.479 ***
                                                       [0.024]          [0.024]         [0.024]
Δ mpr                                                    0.228 ***       0.436 ***       0.437 ***
                                                       [0.041]          [0.069]         [0.069]
Δ ir (t-1)                                              -0.058 ***      -0.058 **       -0.059 **
                                                       [0.016]          [0.027]         [0.027]
Δ mpr (t-1)                                              0.161 ***       0.417 ***       0.417 ***
                                                      [0.060]           [0.056]         [0.056]
Calendar Effects
MP Meeting day                                         -0.010 *         -0.018 ***      -0.017 ***
                                                      [0.005]           [0.006]         [0.006]
VAT Payoff day                                         -0.004           -0.001          -0.001
                                                      [0.004]           [0.005]         [0.006]
Pre- End of Maintenance Period                         -0.009 ***       -0.007 *        -0.007 *
                                                      [0.003]           [0.004]         [0.003]
Post- End of Maintenance Period                        0.026     ***     0.027 ***       0.027 ***
                                                      [0.004]           [0.003]         [0.004]
Dummy Lender Bank                                      -0.006 **        -0.007 **       -0.007 **
                                                      [0.003]           [0.003]         [0.003]
Central Bank's Open Market Operations
Δ Injections                                                            -0.184 **       -0.181 **
                                                                        [0.084]         [0.086]
Δ Injections (t-1)                                                        0.13           0.135
                                                                        [0.086]         [0.086]
Δ Drainage                                                               0.725 **        0.702 **
                                                                        [0.319]         [0.328]
Δ Drainage (t-1)                                                         0.679           0.649
                                                                        [0.501]         [0.499]
Δ Net Permanent Facilities                                              -0.541          -0.529
                                                                        [0.627]         [0.630]
Δ Net Permanent Facilities (t-1)                                         0.151           0.219
                                                                        [0.915]         [0.915]
Private Investors Depositors
Δ Overall PFs Deposits                                                                  -0.095
                                                                                        [0.219]
Δ Overall PFs Deposits (t-1)                                                            -0.294
                                                                                        [0.301]
Δ Other Deposits                                                                         0.005
                                                                                        [0.045]
Δ Other Deposits (t-1)                                                                   0.059
                                                                                        [0.044]
Observations                                           3804               3085            3085

Groups                                                   22                 20               20
Robust standard errors in brackets; * significant at 10%; ** significant at 5%; *** significant at
1%. Estimations include individual and monthly fixed effects.




                                                                                                     37
                                      Table A6 (Extended Table 8)
                              Testing Asymmetry; Dependent Variable:                Δirit
                                  Sample Period: June 2006 to August 2008


                                                            [1]                       [2]                       [3]

                                                     Illiquid Market            Liquid Market

                                                        ir > mpr                  ir < mpr                      Chi2
ir (t-1) - mpr (t-1)                                              -0.547 ***                -0.450 ***                [207.4] ***
                                                                  [0.035]                   [0.060]
Δ mpr                                                              0.982 ***                 0.074 *                  [127.1] ***
                                                                  [0.086]                   [0.038]
Δ ir (t-1)                                                         0.001                    -0.106 ***                 [4.90] **
                                                                  [0.030]                   [0.041]
Δ mpr (t-1)                                                        0.083                     0.163 *                   [4.52] **
                                                                  [0.083]                   [0.098]
Central Bank's Open Market Operations
Δ Injections                                                      -0.096                     0.000                     [0.19]
                                                                  [0.136]                   [0.139]
Δ Injections (t-1)                                                 0.125                    -0.119                     [0.00]
                                                                  [0.098]                   [0.179]
Δ Drainage                                                         0.088                     0.765 ***                 [2.97] *
                                                                  [0.417]                   [0.283]
Δ Drainage (t-1)                                                   0.065                     1.709 ***                 [4.93] **
                                                                  [0.521]                   [0.569]
Private Investors Depositors
Δ Overall PFs Deposits                                             0.039                     0.400                     [0.62]
                                                                  [0.241]                   [0.440]
Δ Overall PFs Deposits (t-1)                                      -0.442                    -0.380                     [1.55]
                                                                  [0.394]                   [0.354]
Δ Other Deposits                                                   0.067                    -0.267                     [0.91]
                                                                  [0.047]                   [0.188]
Δ Other Deposits (t-1)                                             0.120 **                 -0.139                     [0.01]
                                                                  [0.057]                   [0.192]
Observations                                                                             3059

Groups                                                                                      20

Notes: Robust standard errors in brackets; * significant at 10%; ** significant at 5%; *** significant at 1%. Estimations include
individual and monthly fixed effects. The equations include the same controls used in the time series IV estimation




                                                                                                                       38
                                      Table A7 (Extended Table 9)
                  Panel IV Estimation by Type of Bank; Dependent Variable:                       Δirit ;
                                  Sample Period: June 2006 to August 2008

                                                          Large Banks              Medium Banks                Small Banks
                                                               [1]                       [2]                          [3]

  ir (t-1) - mpr (t-1)                                           -0.649 ***                  -0.55 ***                 -0.486 ***
                                                                 [0.080]                   [0.034]                     [0.038]
  Δ mpr                                                           0.134                      0.197 ***                  0.299 ***
                                                                 [0.110]                   [0.060]                     [0.085]
  Δ ir (t-1)                                                      0.002                     -0.047                     -0.083 ***
                                                                 [0.104]                   [0.034]                     [0.031]
  Δ mpr (t-1)                                                     0.185                        0.08                         0.21 **
                                                                 [0.241]                   [0.098]                     [0.103]
Central Bank's Open Market Operations
  Δ Injections                                                   -0.025                     -0.163                     -0.266 *
                                                                 [0.182]                   [0.178]                     [0.150]
  Δ Injections (t-1)                                              0.074                      0.139                      0.212 *
                                                                 [0.132]                   [0.128]                     [0.119]
  Δ Drainage                                                      0.294                      0.687                          1.36 ***
                                                                 [0.287]                   [0.445]                     [0.378]
  Δ Drainage (t-1)                                               -0.439                      0.239                      0.986
                                                                 [1.129]                   [0.368]                     [0.935]
Private Investors Depositors

  Δ Overall PFs Deposits                                         -0.224                      0.338                      0.932
                                                                 [0.543]                   [0.238]                     [1.099]
  Δ Overall PFs Deposits (t-1)                                   -0.347                     -0.233                     -0.189
                                                                 [0.685]                   [0.214]                     [1.120]
  Δ Other Deposits                                               -0.053                      0.042                      0.173
                                                                 [0.110]                   [0.053]                     [0.156]
  Δ Other Deposits (t-1)                                          0.049                      0.012                      0.047
                                                                 [0.111]                   [0.086]                     [0.145]
Observations                                                          497                      1650                         1395

Groups                                                                  4                          9                           7


Notes: Robust standard errors in brackets; * significant at 10%; ** significant at 5%; *** significant at 1%. Estimations include
individual and monthly fixed effects. The equations include the same controls used in the time series IV estimation




                                                                                                                        39
       Documentos de Trabajo                                      Working Papers
       Banco Central de Chile                                   Central Bank of Chile

          NÚMEROS ANTERIORES                                             PAST ISSUES

La serie de Documentos de Trabajo en versión PDF puede obtenerse gratis en la dirección electrónica:
www.bcentral.cl/esp/estpub/estudios/dtbc. Existe la posibilidad de solicitar una copia impresa con
un costo de $500 si es dentro de Chile y US$12 si es para fuera de Chile. Las solicitudes se pueden hacer
por fax: (56-2) 6702231 o a través de correo electrónico: bcch@bcentral.cl.

Working Papers in PDF format can be downloaded free of charge from:
www.bcentral.cl/eng/stdpub/studies/workingpaper. Printed versions can be ordered individually
for US$12 per copy (for orders inside Chile the charge is Ch$500.) Orders can be placed by fax: (56-2)
6702231 or e-mail: bcch@bcentral.cl.

DTBC-515                                                                                   Abril 2009
Sovereign Defaulters: Do International Capital Markets Punish
Them?
Miguel Fuentes y Diego Saravia

DTBC-514                                                                                   Abril 2009
En Búsqueda de un Buen Benchmark Predictivo para la Inflación
Pablo Pincheira y Álvaro García

DTBC-513                                                                                  Marzo 2009
From Crisis to IMF-Supported Program: Does Democracy Impede
the Speed Required by Financial Markets?
Ashoka Mody y Diego Saravia

DTBC-512                                                                                Diciembre 2008
A Systemic Approach to Money Demand Modeling
Mauricio Calani, Rodrigo Fuentes y Klaus Schmidt-Hebbel

DTBC-511                                                                                Diciembre 2008
Forecasting Inflation in Difficult Times
Juan Díaz y Gustavo Leyva

DTBC-510                                                                                Diciembre 2008
Overoptimism, Boom-Bust Cycles, and Monetary Policy in Small
Open Economies
Manuel Marfán, Juan Pablo Medina y Claudio Soto

DTBC-509                                                                                Diciembre 2008
Monetary Policy Under Uncertainty and Learning: An Overview
Klaus Schmidt-Hebbel y Carl E. Walsh

DTBC-508                                                                                Diciembre 2008
Estimación de Var Bayesianos para la Economía Chilena
Patricio Jaramillo
DTBC-507                                                           Diciembre 2008
Chile’s Growth and Development: Leadership, Policy-Making
Process, Policies, and Results
Klaus Schmidt-Hebbel

DTBC-506                                                           Diciembre 2008
Exit in Developing Countries: Economic Reforms and Plant
Heterogeneity
Roberto Álvarez y Sebastián Vergara

DTBC-505                                                           Diciembre 2008
Evolución De La Persistencia Inflacionaria En Chile
Pablo Pincheira

DTBC-504                                                           Noviembre 2008
Robust Learning Stability with Operational Monetary Policy Rules
George W. Evans y Seppo Honkapohja

DTBC-503                                                           Noviembre 2008
Riesgo de Crédito de la Banca
Rodrigo Alfaro, Daniel Calvo y Daniel Oda


DTBC-502                                                            Octubre 2008
Determinacy, Learnability, And Plausibility In Monetary Policy
Analysis: Additional Results
Bennett T. McCallum


DTBC-501                                                            Octubre 2008
Expectations, Learning, And Monetary Policy: An Overview Of
Recent Research
George W. Evans y Seppo Honkapohja


DTBC-500                                                            Octubre 2008
Higher Order Properties of the Symmetrically Normalized
Instrumental Variable Estimator
Rodrigo Alfaro


DTBC-499                                                            Octubre 2008
Imperfect Knowledge And The Pitfalls Of Optimal Control
Monetary Policy
Athanasios Orphanides y John C. Williams